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Cloud edge-end resource collaborative scheduling method driven by spatio-temporal data visualization task

A spatiotemporal data, task-driven technology, applied in resource allocation, electrical digital data processing, multi-programming devices, etc., can solve the problems of low efficiency of spatiotemporal data visualization

Active Publication Date: 2021-06-25
SHENZHEN UNIV
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Problems solved by technology

[0005] The main purpose of the present invention is to provide a space-time data visualization task-driven collaborative scheduling method for cloud-side-device resources, aiming to solve the problem of low efficiency of space-time data visualization in the prior art

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  • Cloud edge-end resource collaborative scheduling method driven by spatio-temporal data visualization task
  • Cloud edge-end resource collaborative scheduling method driven by spatio-temporal data visualization task
  • Cloud edge-end resource collaborative scheduling method driven by spatio-temporal data visualization task

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0035] The spatio-temporal data visualization task-driven cloud-edge resource collaborative scheduling method described in the preferred embodiment of the present invention can be executed by an intelligent terminal. In this embodiment, the security management process is described by taking installation on a smart terminal as an example. Such as figure 1 Said, the cloud-side-end resource collaborative scheduling method driven by the spatio-temporal data visualization task includes the following steps:

[0036] In step S100, the resource information stored in the cloud edge terminal is ...

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Abstract

The invention discloses a cloud side end resource collaborative scheduling method driven by a spatio-temporal data visualization task. The method comprises the following steps of: servitizing resource information of a cloud side end to obtain a service task corresponding to the resource information; when a spatio-temporal data visualization task is obtained, performing task decomposition on the spatio-temporal data visualization task to obtain a scheduling workflow corresponding to the spatio-temporal data visualization task; taking a service task corresponding to the scheduling workflow as a service unit, and connecting the service unit to obtain a scheduling service chain corresponding to the spatio-temporal data visualization task; and dynamically allocating the resource information and executing the scheduling service chain according to the scheduling service chain. Through servitization of the resource information and decomposition of the spatio-temporal data visualization task, the resource information corresponds to the service, allocation of the resource information is carried out according to the situation of the task, and efficient execution of the visualization task is achieved.

Description

technical field [0001] The present invention relates to the technical field of spatio-temporal data visualization, in particular to a method for collaborative scheduling of cloud-edge-device resources driven by spatio-temporal data visualization tasks. Background technique [0002] With the rapid increase of sensing equipment and the accumulation of time, spatio-temporal data becomes larger and larger. With the rapid development of technologies such as geographic information, big data and data visualization, and the promotion of field informatization projects, the dynamics of spatio-temporal big data Analytics has become a critical need today. At present, the visualization and scheduling methods of spatio-temporal scenes mainly rely on the establishment of spatial index, dynamic data scheduling and data simplification and other optimization methods. For example, for large-scale massive terrain rendering, high efficiency is mainly achieved by building terrain pyramids and dyn...

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Application Information

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IPC IPC(8): G06F9/50
CPCG06F9/5083G06F2209/5017
Inventor 李晓明刘铭崴王伟玺谢林甫汤圣君李游郭仁忠
Owner SHENZHEN UNIV
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